ITM Web Conf.
Volume 47, 20222022 2nd International Conference on Computer, Communication, Control, Automation and Robotics (CCCAR2022)
|Number of page(s)||10|
|Section||Algorithm Optimization and Application|
|Published online||23 June 2022|
Research on an improved fish recognition algorithm based on YOLOX
1 Hainan University, College of Information and Communication Engineering, China
2 College of Information and Communication Engineering, Hainan University, Haikou, China
* Corresponding author: email@example.com
The key to the development of underwater resources is to detect underwater targets quickly and accurately in real time. However, due to the influence of light, the underwater image is easy to be distorted and the contrast is low and so on, which greatly affects the performance of the detection algorithm, In order to improve the detection accuracy of underwater targets, After a detailed analysis of the underwater detection target features, The attention mechanism ECA module was added to the YOLOX model, Real-ESRGAN was used to treat multiple target and fuzzy images in detection images, the accuracy improved about 10 percent, A high-precision target detection algorithm suitable for underwater fish was developed, The ideal detection result was achieved.
Key words: Deep learning / Underwater target detection / YOLOX / Attention mechanism ECA / ESRGAN
© The Authors, published by EDP Sciences, 2022
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